A network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes.

ABSTRACT:

Background

The rapid collection of diverse genome-scale data raises the urgent need to integrate and utilise these resources for biological discovery or biomedical applications. For example, diverse transcriptomic and gene copy number variation data are currently collected for various cancers, but relatively few current methods are capable to utilise the emerging information.

Methods

We developed and tested a data-integration method to identify gene networks that drive the biology of breast cancer clinical subtypes. The method simultaneously overlays gene expression and gene copy number data on protein-protein interaction, transcriptional-regulatory and signalling networks by identifying coincident genomic and transcriptional disturbances in local network neighborhoods.

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SUBMITTER: Dutta B 

PROVIDER: S-EPMC3304402 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature